TY  - JOUR
T1  - The Use of Exploratory Graph Analysis to Validate Trust in Relationships Scale
TT  - The Use of Exploratory Graph Analysis to Validate Trust in Relationships Scale
AU  - Avcu, Akif
PY  - 2021
DA  - September
DO  - 10.21449/ijate.831784
JF  - International Journal of Assessment Tools in Education
JO  - Int. J. Assess. Tools Educ.
PB  - İzzet KARA
WT  - DergiPark
SN  - 2148-7456
SP  - 542
EP  - 552
VL  - 8
IS  - 3
LA  - en
AB  - Today, various methods have been developed with a purpose to determine the number of factors underlying a construct. However, there is no definitive agreement on which techniques to be preferred to extract the underlying dimensions. To this end, Exploratory Graphical Analysis (EGA), a recently proposed method, has been compared with traditional methods and the results have revealed that the EGA is less affected from conditions like sample size and inter-dimensional correlation. Besides, it provides more stable results across different conditions. Considering the attractive opportunities it offers, this method has taken its place in the literature as a remarkable alternative to traditional methods. The EGA provides unique outputs compared to other factor extraction techniques. Considering this, interpreting the results obtained within this new and promising framework is assumed to contribute to validation studies. Based on this reality, this study aims to apply the EGA method to Trust in Relations Scale (TRS) and therefore to contribute to its validity. The investigation of TRS’s reliability and validity has already been documented, presenting research opportunities to researchers in the field of positive psychology. The results revealed that, the EGA produces dimensionality structures identical to confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). In addition, further psychometrical indicators within the framework of network analysis are provided. The findings of the study are believed to contribute to the validity of the already existing Trust in Relationships Scale.
KW  - trust in relationships
KW  - exploratory graph analysis
KW  - network psychometrics
N2  - Today, various methods have been developed with a purpose to determine the number of factors underlying a construct. However, there is no definitive agreement on which techniques to be preferred to extract the underlying dimensions. To this end, Exploratory Graphical Analysis (EGA), a recently proposed method, has been compared with traditional methods and the results have revealed that the EGA is less affected from conditions like sample size and inter-dimensional correlation. Besides, it provides more stable results across different conditions. Considering the attractive opportunities it offers, this method has taken its place in the literature as a remarkable alternative to traditional methods. The EGA provides unique outputs compared to other factor extraction techniques. Considering this, interpreting the results obtained within this new and promising framework is assumed to contribute to validation studies. Based on this reality, this study aims to apply the EGA method to Trust in Relations Scale (TRS) and therefore to contribute to its validity. The investigation of TRS’s reliability and validity has already been documented, presenting research opportunities to researchers in the field of positive psychology. The results revealed that, the EGA produces dimensionality structures identical to confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). In addition, further psychometrical indicators within the framework of network analysis are provided. The findings of the study are believed to contribute to the validity of the already existing Trust in Relationships Scale.
CR  - Al-Salom, P., & Miller, C. J. (2017). The problem with online data collection: predicting invalid responding in undergraduate samples. Modern Psychological Studies, 22(2), 2. doi: 10.1007/s12144-017-9674-9
CR  - Al-Salom, P., & Miller, C. J. (2017). The problem with online data collection: predicting invalid responding in undergraduate samples. Modern Psychological Studies, 22(2), 2. doi: 10.1007/s12144-017-9674-9
CR  - Bandalos, D. L., & Boehm-Kaufman, M. R. (2009). Four common misconceptions in exploratory factor analysis. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences (p. 61–87). Routledge/Taylor & Francis Group.
CR  - Bandalos, D. L., & Boehm-Kaufman, M. R. (2009). Four common misconceptions in exploratory factor analysis. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences (p. 61–87). Routledge/Taylor & Francis Group.
CR  - Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York, NY: Plenum Press.
CR  - Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York, NY: Plenum Press.
CR  - Chen, J., Chen, Z., (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95, 759-771. doi: 10.1093/biomet/asn034
CR  - Chen, J., Chen, Z., (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95, 759-771. doi: 10.1093/biomet/asn034
CR  - Christensen, A. P., Golino, H. F., & Silvia, P. (2019). A psychometric network perspective on the measurement and assessment of personality traits. PsyArXiv. doi:10.31234/osf.io/ktejp.
CR  - Christensen, A. P., Golino, H. F., & Silvia, P. (2019). A psychometric network perspective on the measurement and assessment of personality traits. PsyArXiv. doi:10.31234/osf.io/ktejp.
CR  - Christensen, A. P., & Golino, H. (2021). On the equivalency of factor and network loadings. Behavior research methods, Advance online publication. doi:10.3758/s13428-020-01500-6
CR  - Christensen, A. P., & Golino, H. (2021). On the equivalency of factor and network loadings. Behavior research methods, Advance online publication. doi:10.3758/s13428-020-01500-6
CR  - Demirci, İ. & Ekşi. H. (2018). Keep calm and be happy: A mixed method study from character strengths to well-being. Educational Sciences: Theory & Practice, 18(29) 303–354. doi: 10.12738/estp.2018.2.0799
CR  - Demirci, İ. & Ekşi. H. (2018). Keep calm and be happy: A mixed method study from character strengths to well-being. Educational Sciences: Theory & Practice, 18(29) 303–354. doi: 10.12738/estp.2018.2.0799
CR  - Demirci, İ., Ekşi, H., Dinçer, D. ve Kardaş, S. (2017). Beş boyutlu iyi oluş modeli: PERMA Ölçeği’nin Türkçe formunun geçerlik ve güvenirliği. The Journal of Happiness & Well-Being, 5(1), 60-77.
CR  - Demirci, İ., Ekşi, H., Dinçer, D. ve Kardaş, S. (2017). Beş boyutlu iyi oluş modeli: PERMA Ölçeği’nin Türkçe formunun geçerlik ve güvenirliği. The Journal of Happiness & Well-Being, 5(1), 60-77.
CR  - Epskamp, S., & Fried, E.I. (2016). A tutorial on estimating regularized partial correlation networks. PsyArXiv.1607.01367.
CR  - Epskamp, S., & Fried, E.I. (2016). A tutorial on estimating regularized partial correlation networks. PsyArXiv.1607.01367.
CR  - Epskamp, S., Rhemtulla, M., Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82, 904-927. doi:10.1007/s11336-017-9557-x
CR  - Epskamp, S., Rhemtulla, M., Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82, 904-927. doi:10.1007/s11336-017-9557-x
CR  - Garcia-Garzon, E., Abad, F. J., & Garrido, L. E. (2019b). Searching for g: A new evaluation of spm-ls dimensionality. Journal of Intelligence, 7(3), 14.  doi:10.3390/jintelligence7030014.
CR  - Garcia-Garzon, E., Abad, F. J., & Garrido, L. E. (2019b). Searching for g: A new evaluation of spm-ls dimensionality. Journal of Intelligence, 7(3), 14.  doi:10.3390/jintelligence7030014.
CR  - Garrido, L. E., Abad, F. J., & Ponsoda, V. (2013). A new look at horn’s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454–74. doi:10.1037/a0030005
CR  - Garrido, L. E., Abad, F. J., & Ponsoda, V. (2013). A new look at horn’s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454–74. doi:10.1037/a0030005
CR  - Golino, H., & Christensen, A. P. (2020). EGAnet: Exploratory Graph Analysis -- A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package version 0.9.4.
CR  - Golino, H., & Christensen, A. P. (2020). EGAnet: Exploratory Graph Analysis -- A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package version 0.9.4.
CR  - Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PloS One, 12(6), e0174035. doi:10.1371/journal.pone.0174035
CR  - Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PloS One, 12(6), e0174035. doi:10.1371/journal.pone.0174035
CR  - Golino, H., Shi, D., Garrido, L.E., Christensen, A.P., Nieto, M.D., Sadana, R., Thiyagarajan, J.A. & Martinez-Molina, A. (2018, December 19). Investigating the performance of Exploratory Graph Analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. doi:10.31234/osf.io/gzcre
CR  - Golino, H., Shi, D., Garrido, L.E., Christensen, A.P., Nieto, M.D., Sadana, R., Thiyagarajan, J.A. & Martinez-Molina, A. (2018, December 19). Investigating the performance of Exploratory Graph Analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. doi:10.31234/osf.io/gzcre
CR  - Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrika, 19, 149-161.doi: 10.1007/BF02289162
CR  - Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrika, 19, 149-161.doi: 10.1007/BF02289162
CR  - Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. doi: 10.1007/BF02289447
CR  - Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. doi: 10.1007/BF02289447
CR  - Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. doi:10.1177/001316446002000116
CR  - Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. doi:10.1177/001316446002000116
CR  - Keith, T. Z., Caemmerer, J. M. & Reynolds, M. R. (2016). Comparison of methods for factor extraction for cognitive test-like data: Which overfactor, which underfactor? Intelligence, 54, 37-54. doi:10.1016/j.intell.2015.11.003
CR  - Keith, T. Z., Caemmerer, J. M. & Reynolds, M. R. (2016). Comparison of methods for factor extraction for cognitive test-like data: Which overfactor, which underfactor? Intelligence, 54, 37-54. doi:10.1016/j.intell.2015.11.003
CR  - Lauritzen, S. L. (1996b). Graphical Models. Oxford Statistical Science Series. volume 17. New York, NY: Oxford University Press.
CR  - Lauritzen, S. L. (1996b). Graphical Models. Oxford Statistical Science Series. volume 17. New York, NY: Oxford University Press.
CR  - Ledesma, R. D., & Valero-Mora, P. (2007). Determining the Number of Factors to Retain in EFA: an easy-to-use computer program for carrying out Parallel Analysis. Practical Assessment, Research & Evaluation, 12(2), 1-11. doi:10.7275/wjnc-nm63
CR  - Ledesma, R. D., & Valero-Mora, P. (2007). Determining the Number of Factors to Retain in EFA: an easy-to-use computer program for carrying out Parallel Analysis. Practical Assessment, Research & Evaluation, 12(2), 1-11. doi:10.7275/wjnc-nm63
CR  - Lubbe, D. (2019). Parallel analysis with categorical variables: Impact of category probability proportions on dimensionality assessment accuracy. Psychological Methods, 24(3), 339–351. doi: 10.1037/met0000171.
CR  - Lubbe, D. (2019). Parallel analysis with categorical variables: Impact of category probability proportions on dimensionality assessment accuracy. Psychological Methods, 24(3), 339–351. doi: 10.1037/met0000171.
CR  - Osborne J.W. & Costello (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2):131-146.
CR  - Osborne J.W. & Costello (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2):131-146.
CR  - Osborne, J., Costello, A. & Kellow, J. (2008). Best practices in exploratory factor analysis. In Osborne, J. (Ed.), Best practices in quantitative methods (pp. 86-99). SAGE Publications, Inc., doi:10.4135/9781412995627
CR  - Osborne, J., Costello, A. & Kellow, J. (2008). Best practices in exploratory factor analysis. In Osborne, J. (Ed.), Best practices in quantitative methods (pp. 86-99). SAGE Publications, Inc., doi:10.4135/9781412995627
CR  - Pons, P., & Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10, 191–218. doi: 10.7155/jgaa.00185
CR  - Pons, P., & Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10, 191–218. doi: 10.7155/jgaa.00185
CR  - R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
CR  - R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
CR  - Raîche, G., Walls, T. A., Magis, D., Riopel, M., & Blais, J.-G. (2013). Non-graphical solutions for Cattell’s scree test. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 23–29. doi:10.1027/1614-2241/a000051
CR  - Raîche, G., Walls, T. A., Magis, D., Riopel, M., & Blais, J.-G. (2013). Non-graphical solutions for Cattell’s scree test. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 23–29. doi:10.1027/1614-2241/a000051
CR  - Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. doi: 10.18637/jss.v048.i02
CR  - Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. doi: 10.18637/jss.v048.i02
CR  - Spearman, C. (1904). "General intelligence" objectively determined and measured. American Journal of Psychology, 15, 201–293. doi: 10.2307/1412107
CR  - Spearman, C. (1904). "General intelligence" objectively determined and measured. American Journal of Psychology, 15, 201–293. doi: 10.2307/1412107
CR  - Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B, 267–288.
CR  - Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B, 267–288.
CR  - Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. doi: 10.1037/a0023353
CR  - Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. doi: 10.1037/a0023353
CR  - van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4, [5918]. doi: 10.1038/srep05918.
CR  - van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4, [5918]. doi: 10.1038/srep05918.
CR  - Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321–327. doi: 10.1007/BF02293557
CR  - Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321–327. doi: 10.1007/BF02293557
CR  - Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D.
CR  - Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D.
CR  - Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (p. 41–71). Kluwer Academic/Plenum Publishers. doi: 10.1007/978-1-4615-4397-8_3.
CR  - Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (p. 41–71). Kluwer Academic/Plenum Publishers. doi: 10.1007/978-1-4615-4397-8_3.
UR  - https://doi.org/10.21449/ijate.831784
L1  - https://dergipark.org.tr/tr/download/article-file/1416686
ER  -